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International Journal on Advances in Systems and Measurements, vol 5 no 3 & 4, year 2012, http://www.iariajournals.org/systems_and_measurements/ SUMO in the EU project CityMobil where different scenarios of (partly) automated cars or personal rapid transit were set up on different scales, from a parking area up to whole cities. On a small scale, the benefits of an autonomous bus system were evaluated. In this scenario, busses are informed about waiting passengers and adapt their routes to this demand. On a large scale, the influence of platooning vehicles was investigated, using the model of a middle-sized city of 100.000 inhabitants. Both simulations showed positive effects of transport automation. V. RECENT EXTENSIONS A. Emission and Noise Modeling Within the iTETRIS project, SUMO was extended by a model for noise emission and a model for pollutant emission and fuel consumption. This was required within the project for evaluating the ecological influences of the developed V2X applications. Both models are based on existing descriptions. 7 models for noise emission and 15 pollutant emission / fuel consumption models were evaluated, first. The parameter they need and their output were put against values available within the simulation and against the wanted output, respectively. Finally, HARMONOISE [40] was chosen as noise emission model. Pollutant emission and fuel consumption is implemented using a continuous model derived from values stored in the HBEFA database [41]. The pollutant emission model’s implementation within SUMO allows to collect the emissions and fuel consumption of a vehicle over the vehicle’s complete ride and to write these values into a file. It is also possible to write collected emissions for lanes or edges for defined, variable aggregation time intervals. The only available noise output collects the noise emitted on lanes or edges within predefined time intervals, a per-vehicle noise collecting output is not available. Additionally, it is possible to retrieve the noise, emitted pollutants, and fuel consumption of a vehicle in each time step via TraCI, as well as to retrieve collected emissions, consumption, and noise level for a lane or a road. Besides measuring the level of emissions or noise for certain scenarios, the emission computation was also used for investigating new concepts of vehicle routing and dependencies between the traffic light signal plans and emissions [42]. B. Person-based Intermodal Traffic Simulation A rising relevance of intermodal traffic can be expected due to ongoing urbanization and increasing environmental concerns. To accommodate this trend SUMO was extended by capabilities for simulating intermodal traffic. We give a brief account of the newly added concepts. The conceptual center of intermodal traffic is the individual person. This person needs to undertake a series of trips where each may be taken with a different mode of transport such as personal car, public bus or walking. Trips may include traffic related delays, such as waiting in a jam, waiting for a bus or waiting to pick up an additional passenger. It is important to note that earlier delays influence later trips of a simulated person. The above concept is reflected in an extension of the SUMO route input. One can now specify a person as a list of rides, stops and walks. A ride can stand for any vehicular transportation, both private and public. It is specified by giving a starting edge, ending edge and a specification of the allowed vehicles. Stops correspond to non-traffic related activities such as working or shopping. A walk models a trip taken by foot but it can also stand for other modes of transport that do not interfere with road traffic. Another extension concerns the vehicles. In addition to their route, a list of stops and a line attribute can be assigned. Each stop has a position, and a trigger which may be either a fixed time, a waiting time or the id of a person for which the vehicle must wait. The line attribute can be used to group multiple vehicles as a public transport route. These few extensions are sufficient to express the above mentioned person trips. They are being used within the TAPAS [43][44] project to simulate intermodal traffic for the city of Berlin. Preliminary benchmarks have shown that the simulation performance is hardly affected by the overhead of managing persons. In the future the following issues will be addressed: • Online rerouting of persons. At the moment routing across trips must be undertaken before the start of the simulation. It is therefore not possible to compensate a missed bus by walking instead of waiting for the next bus. • Smart integration of bicycles. Depending on road infrastructure bicycle traffic may or may not interact with road traffic. • Import modules for importing public time tables. VI. CURRENT DEVELOPMENT As shown, the suite covers a large variety of functionalities, and most of them are still under research. In the past, applications from the SUMO suite were adapted to currently investigated projects’ needs, while trying to keep the already given functionality work. This development context will be kept for the next future, and major changes in functionality are assumed to be grounded on the investigated research questions. Nonetheless, a set of “strategic” work topics exist and will be presented in the following sub-sections. They mainly target on increasing the simulation’s validity as well as the number of situations the simulation is able to replicate, and on establishing the simulation as a major tool for evaluation of academic models and algorithms for both traffic simulation as well as for evaluation of traffic management applications. A. Car-Following and Lane-Change API One of the initial tasks SUMO was developed for was the comparison of traffic flow models, mainly microscopic carfollowing and lane-changing models. This wish requires a clean implementation of the models to evaluate. Within the iTETRIS project, first steps towards using other models than 2012, © Copyright by authors, Published under agreement with <strong>IARIA</strong> - www.iaria.org 136
International Journal on Advances in Systems and Measurements, vol 5 no 3 & 4, year 2012, http://www.iariajournals.org/systems_and_measurements/ the used Krauß extension for computing the vehicles’ longitudinal movement were taken by implementing an API for embedding other car-following models. Some initial implementations of other models exist, though not all of them are able to deal correctly with multi-lane urban traffic. What is already possible to do with car-following models is also meant to be implemented for lane-change models. B. Model Improvements While evaluation of academic driver behavior models is one of the aimed research topics, most models are concentrating to describe a certain behavior, e.g., spontaneous jams, making them inappropriate to be used within complex scenarios which contain a large variety of situations. In conclusion, next steps of SUMO development will go beyond established car-following models. Instead, an own model will be developed, aiming on its variability mainly. C. Interoperability SUMO is not the only available open source traffic simulation platform. Some other simulators, such as MATsim, offer their own set of tools for demand generation, traffic assignment etc. It is planned to make these tools being usable in combination with SUMO by increasing SUMO’s capabilities to exchange data. Besides connecting with other traffic simulation packages, SUMO is extended for being capable to interact with driving or world simulators. Within the DLR project “SimWorld Urban”, SUMO is connected to the DLR driver simulator, allowing to perform simulator test drives through a full-sized and populated city area. VII. SUMMARY We have presented a coarse overview of the microscopic traffic simulation package SUMO, presenting the included applications along with some common use cases, and the next development steps. The number of projects and the different scales (from single junction traffic light control to whole city simulation) present the capabilities of the simulation suite. Together with its import tools for networks and demand and recently added features such as emission modeling and the powerful TraCI interface, SUMO aims to stay one of the most popular simulation platforms not only in the field of vehicular communication. We kindly invite the reader to participate in the ongoing development and implement his or her own algorithms and models. Further information can be obtained via the project’s web site [2]. REFERENCES [1] M. Behrisch, L. Bieker, J. Erdmann, and D. Krajzewicz, “SUMO - Simulation of Urban MObility: An Overview,” in SIMUL 2011, The Third International Conference on Advances in System Simulation, 2011. [2] DLR and contributors, SUMO Homepage [Online], http://sumo.sourceforge.net/, accessed July 03, 2012. [3] PTV AG, Vissim homepage [Online], http://www.ptvvision.com/en-uk/products/vision-traffic-suite/ptvvissim/overview/, accessed July 03, 2012. [4] OpenDRIVE consortium, OpenDRIVE homepage [Online], http://www.opendrive.org/, accessed July 03, 2012. [5] PTV AG, VISUM homepage [Online], http://www.ptvvision.com/de/produkte/vision-traffic-suite/ptv-visum/, accessed July 03, 2012. [6] MATSim homepage [Online], http://www.matsim.org/, accessed July 03, 2012. [7] OpenStreetMap homepage [Online], http://www.openstreetmap.org/, accessed July 03, 2012. [8] D. Krajzewicz, G. Hertkorn, J. Ringel, and P. Wagner, “Preparation of Digital Maps for Traffic Simulation; Part 1: Approach and Algorithms,” in Proceedings of the 3rd Industrial Simulation Conference 2005, pp. 285–290. EUROSIS-ETI. 3rd Industrial Simulation Conference 2005, Berlin (Germany). ISBN 90-77381-18-X. [9] L. G. Papaleondiou and M. D. Dikaiakos, “TrafficModeler: A Graphical Tool for Programming Microscopic Traffic Simulators through High-Level Abstractions,” in Proceedings of the 69th IEEE Vehicular Technology Conference, VTC Spring 2009, Spain, 2009. [10] S. Krauß, “Microscopic Modeling of Traffic Flow: Investigation of Collision Free Vehicle Dynamics,” PhD thesis, 1998. [11] E. Brockfeld, R. Kühne, and P. Wagner, “Calibration and Validation of Microscopic Traffic Flow Models,” in Transportation Research Board [ed.]: TRB 2004 Annual Meeting, pp. 62–70, TRB Annual Meeting, Washington, DC (USA) 2004. [12] E. Brockfeld and P. Wagner, “Testing and Benchmarking of Microscopic Traffic Flow Models,” in Proceedings of the 10th World Conference on Transport Research, pp. 775-776, WCTR04 - 10th World Conference on Transport Research, Istanbul (Turkey) 2004. [13] E. Brockfeld, R. Kühne, and P. Wagner, “Calibration and Validation of Microscopic Traffic Flow Models,” Transportation Research Records, 1934, pp. 179–187, 2005. [14] M. Treiber and D. Helbing, “Realistische Mikrosimulation von Strassenverkehr mit einem einfachen Modell,” Symposium Simulationstechnik (ASIM), 2002. [15] B. Kerner, S. Klenov, and A. Brakemeier, “Testbed for wireless vehicle communication: A simulation approach based on three-phase traffic theory,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV’08), pp. 180–185, 2008. [16] R. Wiedemann, „Simulation des Straßenverkehrsflußes,“ in Heft 8 der Schriftenreihe des IfV, Institut für Verkehrswesen, Universität Karlsruhe, 1974. [17] D. Krajzewicz, “Traffic Simulation with SUMO - Simulation of Urban Mobility,” in J. Barceló, “Fundamentals of Traffic Simulation,” International Series in Operations Research and Management Science. Springer, pp. 269–294, ISBN 978-1- 4419-6141-9. ISSN 0884-8289, 2010. [18] A. Wegener, M. Piórkowski, M. Raya, H. Hellbrück, S. Fischer, and J.-P. Hubaux, “TraCI: An Interface for Coupling Road Traffic and Network Simulators,” in Proceedings of the 11th communications and networking simulation symposium, 2008. [19] Politecnico di Torino, TraCI4J Homepage [Online], http://sourceforge.net/apps/mediawiki/traci4j/index.php?title= Main_Page, accessed July 09, 2012. [20] C. Sommer, Z. Yao, R. German, and F. Dressler, “On the need for bidirectional coupling of road traffic microsimulation and network simulation,” in Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models, pp. 41–48, 2008. [21] ns3 Homepage [Online], http://www.nsnam.org/, accessed January 26, 2011. 2012, © Copyright by authors, Published under agreement with <strong>IARIA</strong> - www.iaria.org 137
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